A major constraint for many mobile applications (e.g., mobile TV, VOD (Voice on Demand)) is the limited capacity and lifetime of the batteries of mobile devices. It is reported that in a small-size mobile device like a PDA (Personal Digital Assistant), the percentage of power drained by the wireless interface is up to 50% of the overall system consumption. Without a power management module on the wireless interface, the energy of a mobile device can be drained out quickly. Therefore, energy management of wireless interface has become an important issue.
In view of the above issue, a sleep mode was proposed for wireless networks, in which ideally a mobile station (MS) will power down its wireless interface with a base station (BS) to enter into a sleep state when there is no data for it to receive or transmit, and wake up only when there is data for it. The sleep mode intends to minimize MS power consumption and decrease usage of BS air interface resources. It is also a main task of the energy management to schedule the state (i.e. sleep or wakeup) transition of the wireless interface of the MS in order to minimize its energy consumption because the state transition between sleep and wakeup will also consume energy. In order to reduce the frequency of state transitions, a solution was proposed for the sleep mode to buffer and deliver data in a burst manner, for example, by the slicing technique of DVB-H.
FIG. 1 is an exemplary diagram showing a scheduling method with a burst manner for power-saving of a MS in wireless network in the prior art. FIG. 1 (a) shows the sleep mode with an immediate transmission manner for comparison with the sleep mode with the burst manner shown in FIG. 1 (b).
As shown in FIG. 1 (a), the MS enters into a sleep state in sleep time slots and wakes up to send or receive data packets in wakeup time slots indicated by the pulse parts in the FIG. 1 (a). Now referring to FIG. 1 (b), a periodic sleep mode with the burst manner is shown, in which a sleep cycle period for the MS is divided into a sleep window and a listening window. In the sleep window, the MS can power off the corresponding wireless interface or puts the wireless interface at a low power level. In the listening window, the MS wakes up, i.e., powers on the wireless interface to receive and/or send its data packets. Packets, arriving at or destined to the MS, are buffered and then transmitted in a burst manner within the listening window.
Before entering into the periodic sleep mode, the MS negotiates with the BS about the length (in the units of the physical (PHY) frame) of the listening window, the length of the sleep window, and the starting PHY frame from which the MS starts the periodic sleep cycle. As shown in FIG. 1 (b), the sleep window can be set as the maximum packet delay of this MS.
Comparing with the immediate transmission manner, which is shown in FIG. 1 (a), the sleep mode with the burst manner can obviously reduce the frequency of state transitions, which will in turn reduce the power consumption. But on the other hand, this solution will lead to longer packet delay. The trade-off between the power-saving and the packet delay for IEEE 802.11 network was already studied.
However, existing scheduling methods for IEEE802.11 power management can not readily satisfy the objective of saving power and maintaining QoS (Quality of Service) guarantee simultaneously in such wireless network as IEEE802.16e, where QoS requirements are explicitly specified.
In addition, for IEEE 802.16e systems, existing research only focuses on adaptive sleep mechanisms for web browsing service and on single-MS environments. However, in practical operation, there is usually more than one MS in the regime of a BS.
As described above, the sleep mode is used in wireless networks for power saving of the MSs. Full information regarding the sleep mode is given in the IEEE standard “IEEE802.16e-2005”.
In a wireless network having multiple MSs associated with a BS, the transmission of traffic of these MSs will be influenced from each other because the system radio resource is shared among all these MSs instead of being dedicated to one MS among them. FIG. 2 is a diagram showing resource collision in a multi-MSs wireless network in the prior art. In FIG. 2, three mobile stations MS1, MS2 and MS3 are shown, assigned with the sleep cycle periods of 5, 11 and 18 time slots respectively according to the traditional power-efficient scheduling method for a single-MS environment. In each sleep cycle period, the pulse parts denote the time slots of the listening window for this MS. The sleep cycle period is generally less than the maximum packet delay requirement of an application running on the MS. Otherwise, the QoS requirements of the service cannot be guaranteed.
As shown in FIG. 2, under the time divisional protocol, one time slot can only be allocated to one MS as the listening window. If the time slot 10 is allocated to MS1 as listening window to satisfy its power-saving schedule, the schedule of MS2 cannot be satisfied at the same time. Otherwise, a resource collision will take place for time slot 10, as marked by black parts in FIG. 2. This kind of collision also takes place at time slots 35, 54 and 55. Therefore, the design of a good power-saving scheduling algorithm with Quality of Service (QoS) guarantee for multi-MSs environment is of more practical importance but also more complex.
For the IEEE 802.16e network, several scheduling approaches were proposed to carry out a power-saving schedule of multiple MSs and at the same time maintain the QoS guarantee.
In an approach 1 described by a paper “Improving mobile station energy efficiency in IEEE 802.16e WMAN by burst scheduling, G. Fang, E. Dutkiewicz, Y. Sun, J. Zhou, J. Shi, Z. Li, IEEE Globecom, 2006”, the MS that has the shortest time to reach its maximum bit rate requirement is selected as the primary MS. The scheduler of the BS allocates almost all the bandwidth in a burst to the primary MS and allocates just enough bandwidth to other awake-state MSs to guarantee their minimum data rate requirements.
This approach 1 does not take into consideration real-time services that have packet delay constraints (there is no such constraint for non-real-time services). Some studies show that this approach cannot conserve energy efficiently for TV-like multicast services having static periodic schedule pattern. Besides, it requires a lot of signaling exchanges, which will not only cost bandwidth but also introduce signalling transmission delay. Please note that the types of data delivery services, including the real-time service and non-real-time service, are defined in the above mentioned IEEE801.16-2005 standard, where full information concerning the definition and requirements of each type of services is given.
A paper “Energy efficient integrated scheduling of unicast and multicast traffic in 802.16e WMANs, Lin Tian, et. al., IEEE GLOBECOM 2007” described an approach 2 that proposed to firstly allocated resources to real-time multicast services in a periodic burst manner to save power. In this approach 2, remaining resources are allocated to non-real-time unicast services in an order that resources are firstly allocated to the multicast-group-member MS and then to the MS that only have unicast services. The resource allocated to the unicast service of a multicast-group-member MS is adjacent to the resources for its multicast service. FIG. 3 is an exemplary diagram showing the power-efficient scheduling method of the approach 2. FIG. 3(a) shows resources initially allocated to the unicast and the multicast services for MS1 to MS4 respectively. FIG. 3(b) shows resources allocated to the unicast and the multicast services of each MS are allocated to be adjacent to each other. In fact, the approach 2 assumes that the delay constraints of all the real-time multicast services are the same. It cannot be extended to the general environment where multiple real-time services with different delay constraints (e.g., VoIP and video) exist.
According to an approach 3 in a paper “Energy Efficient Scheduling with QoS Guarantee for IEEE802.16e Broadband Wireless Access Networks Shih-Chang Huang, Rong-Hong Jan, Chien Chen, (2007 IWCMC)”, in a case that multiple MSs have real-time services with different delay constraints, a common sleep cycle period is determined by choosing the minimum delay constraints among all services of the MS. All MSs periodically sleep and wake up to receive their data with the common sleep cycle period. FIG. 4 shows the power-efficient scheduling method of the approach 3. As shown in FIG. 4, the common sleep cycle period in this example is 6 frames long for five MSs A, B, C, D and E. The BS computes the number of frames needed for the MSs it serves. Since one frame slot can only be allocated to one MS, the BS schedules MS E in the 1st frame, and delays the starting times of MS D, C, B and A respectively to the 2nd, 4th, 5th, and 6th frames within each sleeping cycle period. In this way, the allocated frames can be scheduled without overlapping, that is, without resource collision issue.
The advantage of the approach 3 is that it has a simple scheduling algorithm. However, with a common scheduling cycle for all MSs, a MS having larger delay constraints and thus having larger sleep cycle period than the common cycle period will apparently have to perform the state transition more frequently than it is scheduled in the single-MS environment. As described above, state transition between sleep and wakeup will also consume a large amount of energy, which is generally more than one slot unit of energy consumed in wakeup state. Therefore, approach 3 will lead to more energy consumption for the MSs with delay constraints that are larger than the common scheduling period.